{ "anchors": { "agent_arena_ips_score": { "a": -0.25, "b": 0.25, "direction": "higher" } }, "as_of": "2026-11-05", "attributions": [ { "source_id": "arena-leaderboard-dataset", "text": "Arena data: Arena (lmarena-ai), dataset lmarena-ai/leaderboard-dataset, https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset, licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Changes by Inadviser: the Arena scores (the Agent Arena IPS score and the text, text-to-image, text-to-video and search ratings) are rescaled to a 0-100 utility against fixed anchors set by Inadviser; the confidence interval and the observation or vote count are carried over; only a selection of models is shown on each board; where a board shows Arena's cost per task, it is shown unchanged. The dataset maintainers' method applies (https://arena.ai/blog/agent-arena-methodology/ for Agent Arena). Arena does not endorse Inadviser." } ], "board": { "category": "ai-agents", "cost": { "kind": "metric", "label": "Median cost per task", "metric": "cost_per_task_p50", "unit": "USD per task (median)" }, "half_life_days": 30, "job": "Run an AI agent on real software tasks and judge it by how much the agent's own work was kept and corrected, against what each task costs.", "price_limit_days": 30, "products": [ { "id": "claude-opus-5-5-max", "name": "Claude Opus 5.5 (Max)", "vendor": "anthropic" }, { "id": "gemini-4-carbon-high", "name": "Gemini 4 Carbon (High)", "vendor": "google" }, { "id": "claude-sonnet-5-5-max", "name": "Claude Sonnet 5.5 (Max)", "vendor": "anthropic" }, { "id": "gpt-6-astra-max", "name": "GPT-6 Astra (Max)", "vendor": "openai" }, { "id": "claude-fable-5-1-max", "name": "Claude Fable 5.1 (Max)", "vendor": "anthropic" }, { "id": "gpt-6-1-sol-max", "name": "GPT-6.1 Sol (Max)", "vendor": "openai" }, { "id": "gemini-4-argon-high", "name": "Gemini 4 Argon (High)", "vendor": "google" }, { "id": "gpt-6-1-terra-max", "name": "GPT-6.1 Terra (Max)", "vendor": "openai" }, { "id": "muse-wonder-full-max", "name": "Muse Wonder Full (Max)", "vendor": "meta" }, { "id": "claude-fable-5-high", "name": "Claude Fable 5 (High)", "vendor": "anthropic" }, { "id": "claude-opus-5-max", "name": "Claude Opus 5 (Max)", "vendor": "anthropic" }, { "id": "gpt-6-sol-max", "name": "GPT-6 Sol (Max)", "vendor": "openai" }, { "id": "kimi-k3-1-pro-max", "name": "Kimi K3.1 Pro (Max)", "vendor": "moonshot" }, { "id": "gpt-5-6-sol-xhigh", "name": "GPT-5.6 Sol (xHigh)", "vendor": "openai" }, { "id": "claude-sonnet-5-high", "name": "Claude Sonnet 5 (High)", "vendor": "anthropic" }, { "id": "grok-4-7-xhigh", "name": "Grok 4.7 (xHigh)", "vendor": "xai" }, { "id": "gemini-3-8-flash-high", "name": "Gemini 3.8 Flash (High)", "vendor": "google" }, { "id": "muse-wonder-max", "name": "Muse Wonder (Max)", "vendor": "meta" }, { "id": "muse-spark-1-3-max", "name": "Muse Spark 1.3 (Max)", "vendor": "meta" }, { "id": "mimo-v2-6-pro", "name": "MiMo-V2.6-Pro", "vendor": "xiaomi" }, { "id": "deepseek-v4-1-flash-20261017-max", "name": "DeepSeek-V4.1-Flash-20261017 (Max)", "vendor": "deepseek" }, { "id": "gpt-6-luna-max", "name": "GPT-6 Luna (Max)", "vendor": "openai" }, { "id": "glm-5-3-max", "name": "GLM-5.3 (Max)", "vendor": "zai" }, { "id": "hy4-preview", "name": "Hy4 preview", "vendor": "tencent" }, { "id": "kimi-k3-max", "name": "Kimi K3 (Max)", "vendor": "moonshot" }, { "id": "glm-5-2-max", "name": "GLM-5.2 (Max)", "vendor": "zai" }, { "id": "claude-haiku-5-5-high", "name": "Claude Haiku 5.5 (High)", "vendor": "anthropic" }, { "id": "mimo-v2-6-flash", "name": "MiMo-V2.6-Flash", "vendor": "xiaomi" }, { "id": "qwen3-8-max", "name": "Qwen3.8-Max", "vendor": "alibaba" }, { "id": "grok-4-6-xhigh", "name": "Grok 4.6 (xHigh)", "vendor": "xai" }, { "id": "deepseek-v4-pro-high-20260813", "name": "DeepSeek-V4-Pro (High, 20260813)", "vendor": "deepseek" }, { "id": "gpt-5-6-terra-xhigh", "name": "GPT-5.6 Terra (xHigh)", "vendor": "openai" }, { "id": "gemini-3-7-flash-high", "name": "Gemini 3.7 Flash (High)", "vendor": "google" }, { "id": "gpt-6-luna-medium", "name": "GPT-6 Luna (Medium)", "vendor": "openai" }, { "id": "glm-5-3-flash", "name": "GLM-5.3-Flash", "vendor": "zai" }, { "id": "step-5-preview", "name": "Step 5 Preview", "vendor": "stepfun" }, { "id": "minimax-m3-1-flash", "name": "MiniMax-M3.1-Flash", "vendor": "minimax" }, { "id": "qwen3-8-27b", "name": "Qwen3.8-27B", "vendor": "alibaba" }, { "id": "qwen3-8-flash-next", "name": "Qwen3.8-Flash-Next", "vendor": "alibaba" }, { "id": "gemini-3-1-pro-preview", "name": "Gemini 3.1 Pro Preview", "vendor": "google" }, { "id": "beam-1-0-501b-a23b", "name": "Beam 1.0 501B A23B", "vendor": "reflection" }, { "id": "gpt-6-luna-low", "name": "GPT-6 Luna (Low)", "vendor": "openai" }, { "id": "mistral-large-4", "name": "Mistral Large 4", "vendor": "mistral" }, { "id": "qwen3-7-max", "name": "Qwen3.7-Max", "vendor": "alibaba" }, { "id": "qwen3-7-plus", "name": "Qwen3.7-Plus", "vendor": "alibaba" }, { "id": "hy3", "name": "Hy3", "vendor": "tencent" }, { "id": "muse-spark-1-1", "name": "Muse Spark 1.1", "vendor": "meta" }, { "id": "muse-spark-1-2-xhigh", "name": "Muse Spark 1.2 (xHigh)", "vendor": "meta" }, { "id": "mimo-v2-5-pro", "name": "MiMo-V2.5-Pro", "vendor": "xiaomi" }, { "id": "spark-x2-6", "name": "Spark-X2.6", "vendor": "synlan" }, { "id": "minimax-m3", "name": "MiniMax-M3", "vendor": "minimax" }, { "id": "mistral-medium-3-5", "name": "Mistral Medium 3.5", "vendor": "mistral" }, { "id": "nemotron-3-ultra", "name": "Nemotron 3 Ultra", "vendor": "nvidia" }, { "id": "nvidia-nemotron-3-5-super-vl-120b-a12b-nvfp4", "name": "NVIDIA-Nemotron-3.5-Super-VL-120B-A12B (NVFP4)", "vendor": "nvidia" }, { "id": "inkling", "name": "Inkling", "vendor": "thinky" }, { "id": "inkling-small", "name": "Inkling-Small", "vendor": "thinky" }, { "id": "solar-pro-4", "name": "Solar Pro 4", "vendor": "upstage" } ], "question": "Which AI model gives the most useful agent work for the least cost per task?", "region": "global", "requirements": {}, "slug": "ai-agents", "title": "AI coding agents", "workload": { "chars_per_month": null, "unit_note": "One task. Cost is the median cost per task that Arena reports for the model." } }, "code_commit": "6585be527486036d41ec57c349ffe2a97aa8cd24", "decision": { "disqualified": [], "leader": "claude-opus-5-5-max", "margin": 3, "needed": [ { "metric": "agent_arena_ips_score", "need": "another independent origin or repeats", "product": "claude-opus-5-5-max", "type": "narrow_interval", "width": 8.447762 }, { "metric": "agent_arena_ips_score", "need": "another independent origin or repeats", "product": "claude-sonnet-5-5-max", "type": "narrow_interval", "width": 11.140867 }, { "metric": "agent_arena_ips_score", "need": "another independent origin or repeats", "product": "gemini-4-carbon-high", "type": "narrow_interval", "width": 3.222774 } ], "reasons": [ { "code": "bounds_overlap", "gap": 1.045983, "other": "claude-sonnet-5-5-max", "product": "claude-opus-5-5-max", "required": 3 }, { "code": "bounds_overlap", "gap": 1.123185, "other": "gemini-4-carbon-high", "product": "claude-opus-5-5-max", "required": 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"product": "inkling", "q": 17.832904, "rank": 55, "status": "active" }, { "cost": 0.18831, "cost_confirmed": true, "high": 19.948368, "label": "ci95", "low": 12.485999, "product": "inkling-small", "q": 16.217183, "rank": 56, "status": "active" }, { "cost": 0.05355, "cost_confirmed": true, "high": 12.308342, "label": "ci95", "low": 3.912338, "product": "solar-pro-4", "q": 8.11034, "rank": 57, "status": "active" } ], "schema": 1, "seed": null, "site": { "board_note": "Arena data: Arena (lmarena-ai), dataset lmarena-ai/leaderboard-dataset, https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset, licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Changes by Inadviser: the Arena scores (the Agent Arena IPS score and the text, text-to-image, text-to-video and search ratings) are rescaled to a 0-100 utility against fixed anchors set by Inadviser; the confidence interval and the observation or vote count are carried over; only a selection of models is shown on each board; where a board shows Arena's cost per task, it is shown unchanged. The dataset maintainers' method applies (https://arena.ai/blog/agent-arena-methodology/ for Agent Arena). Arena does not endorse Inadviser. Only one origin (Arena) is used, so no board entry can be named Best until a second independent origin or an own test exists. Arena's IPS score comes from agent sessions of its own users; it is not a test of this board's job on your code.", "first_paragraph": "As of 5 November 2026, no option is proven ahead. 3 options of 57 cannot be separated with the evidence in hand: Claude Opus 5.5 (Max), Gemini 4 Carbon (High) and Claude Sonnet 5.5 (Max).", "interval_labels": { "ci95": "built from 95% confidence intervals given by the source" }, "ranking_is_quality_order": true, "ranking_note": "Order is by score point estimate; intervals may overlap.", "sources_used": [ { "checked_on": "2026-11-03", "id": "arena-leaderboard-dataset", "name": "Arena Leaderboard Dataset (lmarena-ai/leaderboard-dataset)", "status": "attribution", "url": "https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset" } ], "verdict_label": "Shortlist" }, "tariff_ids": [], "weights": { "agent_arena_ips_score": 1 } }